The development of information retrieval systems has predominantly focused on improving the overall quality of the search results presented to the user. The quality of the results has typically been measured in terms of precision, recall, or other quantifiable measures of performance. Information retrieval systems, or ‘search engines’ in the context of the Internet and World Wide Web, use a wide variety of techniques to improve the quality and usefulness of the search results. These techniques address every possible aspect of search engine design, from the basic indexing algorithms and document representation, through query analysis and modification, to relevance ranking and result presentation, methodologies too numerous to fully catalog here.
An inherent problem in the design of search engines is that the relevance of search results to a particular user depends on factors that are highly dependent on the user's intent in conducting the search—that is why they are conducting the search—as well as the user's circumstances, the facts pertaining to the user's information need. Thus, given the same query by two different users, a given set of search results can be relevant to one user and irrelevant to another, entirely because of the different intent and information needs. Most attempts at solving the problem of inferring a user's intent typically depend on relatively weak indicators, such as static user preferences, or predefined methods of query reformulation that are nothing more than educated guesses about what the user is interested in based on the query terms. Approaches such as these cannot fully capture user intent because such intent is itself highly variable and dependent on numerous situational facts that cannot be extrapolated from typical query terms.
In part because of the inability of contemporary search engines to consistently find information that satisfies the user's information need, and not merely the user's query terms, users frequently turn to websites that offer additional analysis or understanding of content available on the Internet. For the purposes of discussion these sites are called vertical knowledge sites. Some vertical knowledge websites, typically community sites for users of shared interests, allow users to link to content on the Internet and provide labels or tags describing the content. For example, a site may enable a user to link to the website of an automobile manufacturer, and post comment or description about a particular car being offered by the manufacturer; similarly, such a site could enable a user to link to a news report on the website of a news organization and post comment about the report. These and other vertical knowledge sites may also host the analysis and comments of experts or others with knowledge, expertise, or a point of view in particular fields, who again can comment on content found on the Internet. For example, a website operated by a digital camera expert and devoted to digital cameras typically includes product reviews, guidance on how to purchase a digital camera, as well as links to camera manufacturer's sites, new products announcements, technical articles, additional reviews, or other sources of content. To assist the user, the expert may include comments on the linked content, such as labeling a particular technical article as “expert level,” or a particular review as “negative professional review,” or a new product announcement as “new 10MP digital SLR”. A user interested in a particular point of view, type of information, or the like then search within the domain of such a site for articles or links that have certain associated labels or comments. For example, a user could search the aforementioned digital camera site for all camera reviews labeled “digital SLR”.
One of the underlying aspects of vertical knowledge sites that makes them appealing to users is that some of the users who participate on them come to be perceived as being trustworthy in their comments, analysis, opinions and recommendations. This degree of trust is valuable to users as a way of evaluating the often bewildering array of information that is available on the Internet. Indeed, many popular vertical knowledge sites, blogs, news outlets, so forth, are primarily devoted to facilitating dissemination of the opinions of individual experts or commentators, while other vertical knowledge sites such as forums, rating sites, and community sites operate to share and disseminate the opinions of many users in a community. In either case, many users access these sites because of an underlying sense of trust in at least some of the others users who are providing their opinions. Of course, in some cases a particular user's (or author's) views may not be trusted by others. For example, on most forums there will be one or more users who are viewed by others as being uninformed, biased, hostile or otherwise not trustworthy. Particularly for new users, identifying which other members of a community are trustworthy and which are not can be a difficult and time consuming process.
Some vertical knowledge sites now provide various types of indicators or proxies for the trustworthiness of particular individuals who participate at the site. Auction sites use rating systems to identify trusted buyers and sellers. Forum sites use membership criteria and other factors to distinguish between posters. But many sites simply rely on general reputation of their experts to instill a sense of trust in users who visit the site. Thus, at best a user can currently search within the context or domain of a particular website for comments, opinions or the like made by individuals who are trusted by the user or by others.
The problem remains that when the user returns to a general search engine, outside of the vertical knowledge site, the user is unable to obtain search results that reflect the trustworthiness of the documents themselves or the trustworthiness of any commentary or opinions that may be associated with the search result documents. Thus, none of the additional reputation based information that is associated with users in the vertical knowledge site is available to the general search engine in order to provide more meaningful search results to other users.